| As a new kind of data collection technique, wireless sensor network (WSN) has become one of the hotspot in present information technology field. Wireless sensor node is a tiny device with limited power, and change battery is almost impossible in some applications. This makes the lifetime of nodes mostly depend on the battery, so reduced power consumption to extend the lifetime of network is the primary problem in the research.This thesis carries out a deep research mainly on energy efficient of wireless sensor networks. The main research and contributions are as follows:1. Energy-efficient Clustering Algorithm Based on Pseudo Cluster-head is proposed. In this paper we propose a novel routing algorithm, ECPC, which copes with limited transmission range of each node and brings in a pseudo cluster head to improve the energy efficiency of LEACH. Our solution copes with a fatal drawback of LEACH-each node may have limited transmission range due to energy and hardware limitations. So, data collection at cluster head have to be multi-hop relayed to sink. Further more, simulation results demonstrates our idea. The overall transmitted data and sensor network life time of ECPC is better than that of modified LEACH and much better than original LEACH.2. A Size-constrained Clustering Algorithm (SCA) for Wireless Sensor Network is proposed. By constraining cluster size, the proposed algorithm solves the Hot-Spot problem in Multi-hop Wireless Sensor Networks, which is caused by the unbalanced load of network nodes resulted from their various distances to the base station. By reducing the number of member nodes as well as the volume of data of a cluster, less energy is consumed. It also investigates the problem of reducing the energy cost of the nodes, which are far from a cluster head, by reducing the number of hops. Compared with previous multi-hop clustering algorithms, the proposed SCA algorithm has the following advantage:the unbalanced clustering method reduces the size of a cluster; therefore it reduces the data confliction in the network which helps balance the energy costs of nodes. Simulation shows that the SCA algorithm is superior to the LEACH algorithm in network lifetime.3. An Energy-efficient Clustering algorithm Based on Minimum Dominating Set (ECBD) is presented. This algorithm selects support nodes by received signal strength indicator (RSSI), which solves the decreased throughput problem of the algorithms which select cluster heads simply by node degrees. Using RSSI, only the approximate precise location of a node is required, which can save the communication cost and use the minimal energy cost to maintain the transferring and communication between nodes. Thus, a node costs much less energy to communicate with other nodes in a cluster, and in this way the total energy cost of the entire network is reduced. This algorithm is intrinsically an optimization problem on finding cluster heads, its computational cost is O(log n logâ–³). It selects a cluster head by utilizing the local link information, the link degree to the neighbors, and the remaining energy of a node. Simulation suggests that the ECBD algorithm is superior to the HEED algorithm not only in cluster size, but also in clustering time and in the energy cost per sent messages.4. Two improved algorithms are proposed based on the ECBD algorithm:1) the kECBD algorithm, which allows a node to be added into the cluster in its k-hops. The kECBD algorithm takes advantage of multi-hop communication to reduce the number of cluster head, which reduces the energy cost of a node. Compared with ECBD, it is more flexible in selecting cluster heads, and requires less cluster heads to cover the same number of nodes.2) the iECBD algorithm, which incorporates a running extension mechanism to provide more candidate cluster heads in each round, so that clustering can be finished in less runs. Simulation shows that the performance of these two algorithms is better than that of the HEED algorithm.5. A Circuit Heuristic-based Wireless Sensor Network Energy Saving Policy (CHEP) is discussed. In the case we assumed that the information of the entire network is available, network routing optimization is tackled by a centralized algorithm. Starting from the network topology, this policy models the entire wireless sensor network as a circuit. The circuit network simulation has the characteristic of balancing. If a sensor node sends messages to a node faraway, it corresponds to transmitting large electronic current via a large resistance in a circuit, which prevents a node to transfer long-distance message and so that the energy costs of the nodes are balanced. Simulation suggests that this policy can balance the energy cost of the sensor nodes and hence prolongs the lifespan of the entire network. This thesis presented the idea of this policy and provided simulations on the network life time and node energy distribution.Moreover, in the case that the entire network is observed, considering a typical wireless sensor network model, this thesis defined the concept of a "healthy" network, and proposed the idea of "sphere of interest". It proposed the step-by-step idea of network routing optimization based on the energy of a typical wireless sensor network, and furthermore proposed a method to estimate the upper bound of the global optimization of energy cost. It generated the mathematical problem of finding the optimal route and provided a solution.
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